Development of model-embedded air data instrumentation and sensor integration for advanced unmanned aircraft

先进无人机模型嵌入式空气数据仪器和传感器集成的开发

• 批准号: 2895318
• 金额: --
• 依托单位: University of Surrey
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2895318
• 关键词: Development; model; embedded; air; data

The global market for UAVs has been growing very rapidly, driving forward technology in automation, batteries, materials and measurement. However, one area in which technology appears to be lagging is in air data gathering: the development of probes and sensors which are robust enough to survive rough handling and environmental extremes, and which are capable of providing measurements of velocity, incidence, sideslip, and other critical parameters to the flight data computer. UAV airframers must currently select between large and heavy aircraft Pitot systems and low-quality and unreliable low-cost systems for the hobby market. The purpose of this project, therefore, is to develop the models and data assimilation techniques required to use air data sensors for the specific conditions uniquely experienced by UAVs, and to use these models in a coupled airframe-sensor optimization process to design the next generation of distributed, airframe-integrated air data sensors.

无人机的全球市场一直在迅速发展，推动了自动化，电池，材料和测量方面的前进技术。但是，技术似乎落后的一个领域是空气数据收集：探针和传感器的开发足以在粗糙的处理和极端环境方面生存，并且能够为飞行数据计算机提供速度，入射率，侧滑和其他关键参数的测量。目前，无人机飞机必须在大型和重型飞机皮托特系统以及爱好市场的低质量和不可靠的低成本系统之间进行选择。因此，该项目的目的是开发用于使用无人机独特经历的特定条件所需的模型和数据同化技术，并在耦合机身传感器优化过程中使用这些模型来设计下一代分布式机框，机框架的空气汇总空气数据传感器。